The Nigerian University System and the Challenges of Capacity Building in a Globalized Economy
Bibliographic record
Abstract
Abstract: The scaring effects of globalization and the global economic shift have affected world economic order to the extent that the weak economies are still trying to grapple with the production processes. The necessity of international discourse, alignment and reorganization generated by the new economic order has not provided the needed solution. Rather, the process has continued to erode and reorder the traditional economic activities of the weak economies to the extent that there is unprecedented unemployment. This gives the impression that the university academic system, with the courses and programmes taught, is not structured in a flexible manner to arrest the situation. This paper on the synergy between the Nigerian university academic system and the challenges of capacity building in a globalized economy investigates why, in spite of the numerous international discourses, economic restructuring, etc. unemployment, especially among the products of universities, continues to escalate, economy continues to dwindle, political structures and governance continue to deteriorate. The observation is that the Nigerian university system has failed to achieve, among the beneficiaries, the expected capacity building, intellectual capital and knowledge necessary to drive the economy in this dispensation. The paper recommends inter alia, an overhaul of the Nigerian university system to take care of the critical requirements of current production processes, flexibilization of labour and employment, ensuring that the knowledge and skills acquired are information and communication technology oriented and the development of the power and energy sector because of its regeneration and multiplier effects on job and wealth creation. Key words: Capacity Building; Flexibilization; Intellectual Capital; Nigerian University Academic System; Globalization
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".